1. Field
This disclosure relates to the use of signals obtained from a limb (hand, and/or forearm, etc.) or other portion of the body subject to fine motor control, in medical diagnostics and biometrics, and to the use of electromyography (EMG) signals for medical, biometrics and related uses. The EMG is thereby used for the purposes of biometric assessment.
2. Background
The prior art is rich in various systems and methods in the area of digital handwriting, as well as various systems and methods relating to useful endeavors. In general, most existing systems and methods provide concrete functions, which have a defined response to a defined stimulus. Such systems, while embodying the “wisdom” of the designer, have a particular shortcoming in that their capabilities are limited.
According to the research that was conducted in Haifa University, handwriting problems are also clues to developmental, neurological, behavioral, or medical conditions such as ADHD and Parkinson's disease. Disturbances in handwriting legibility and speed (known as dysgraphia) are problematic for about 10-30% of elementary school-aged children. Many adults who suffer from neuromuscular pathologies of different types (e.g., Parkinson's disease, multiple sclerosis, Alzheimer's disease) also experience progressive deterioration of the quality of their handwriting. Dysgraphic writing has a variety of academic, emotional and social consequences. The comprehensive and detailed characterization of dysgraphia has diagnostic and treatment value, helping clinicians to differentiate between levels of motor involvement, to evaluate the effectiveness of medication and to achieve better techniques for handwriting remediation.